Foster Innovation Through Data-Driven Insights

Digital
transformation is happening. And it’s happening fast. In fact, IDC1 predicts
that in the next three to four years, digital transformation will do more than
change the way enterprises operate. It will reshape the global economy.

Ultimately,
the insights needed to power an enterprise’s digital transformation are
generated through its data and many have been quick to develop strategies
focused on monetizing data or discovering new revenue streams.

However,
delivering on the strategies isn’t always easy. In fact, it is possible only
when the gap between ‘strategy’ and ‘data sources’ is bridged with solutions
that enable a business to connect, analyze, understand, and act to achieve the
desired outcomes.

For example,
if a bank had a 360 view of a customer, it could also enable better fraud
detection, accelerate loan applications or add new services much faster than
before. And it could also transform the customer experience.

Just
imagine, if before the customer even sat down, before they even entered the
bank, the organization already knew all about their credit

and
transaction history, the type of mortgage they choose, and even their social
media activity. If it was possible to bridge the gap between these data sources
to integrate all this information, approving a loan would take a fraction of
the time it ordinarily does.

In practice,
that means taking a process that used to take weeks, or even months – a
frustrating, form-filling nightmare that required re-stating income and asset
information the bank already had – and removing it from the equation by using
smart technology.

That’s the power of digital transformation – a
better customer experience.

As the
example above highlights, organizations are acquiring data from multiple
different sources – structured data, unstructured data, machine data, sensor
data, video data – the list is almost endless.

When you
combine protection and data mobility, you create a way to integrate all data
sources into a single secured data lake. This data then enters a loop where it
is mobilized, enriched, governed, refined, and most importantly, analyzed.
After that, an enterprise is free to focus on protection and applying different
policies to ensure security and governance.